Category Archives: ESI

Traditional eDiscovery Processing is Now Obsolete

By John Patzakis

eDiscovery can be a very expensive process and time consuming when traditional methods are employed. With legacy processes, from the time ESI collection starts, it often takes weeks for the data to finally end up in review. Time is money, and this dramatically increases costs as well as risk.

ESI processing is a dedicated and often expensive step in the EDRM workflow. The majority of ESI processing consists of data culling and filtering, deduplication, text extraction, metadata preservation, and then staging the data for upload into a review platform, often in the form of a load (DAT) file.  Using ESI processing methods that involve on-premise hardware appliances that are not integrated with the collection process and do not integrate with review platforms like Relativity significantly increase cost and time delays. This means practitioners have to spend the often several weeks that are required by other cumbersome solutions through manual collections and multiple hand-offs.

However, the latest in collection technologies will now combine targeted collection with these processing steps that are performed “on the fly” and in the background so that the data is automatically collected, processed and uploaded into a review platform such as Relativity in one fell swoop.

The graphic below is an illustration contrasting the challenges associated with traditional eDiscovery processes, with the far more efficient new paradigm. When you engage in manual collection, and then manual on-premise hardware-based processing, and finally manual upload to review, you are extending the process by often weeks, you are dramatically increasing cost and risk with many manual data handoffs.

Providing a contrast to traditional methods, a recent Relativity webinar featured the integration of the X1 Distributed Discovery platform with its RelativityOne Collect solution. A live demonstration performed by Relativity Product Manager Greg Evans highlighted in real time how the integration dramatically improves the enterprise eDiscovery process by enabling a targeted and efficient search and collection process, with full and integrated ESI processing. Within minutes, data collected from endpoints with X1 is populated straight into a Relativity workspace, fully processed and ready for review, without any human interaction once the collection is started.

So in terms of the big picture, this X1/Relativity integration not only streamlines enterprise ESI collection, but it relegates ESI processing to a completely automated background function as an afterthought. That’s what disruption looks like.

A recording of the X1/Relativity integration webinar can be accessed here.

Leave a comment

Filed under Best Practices, collection, eDiscovery, Enterprise eDiscovery, ESI, Uncategorized

Relativity Highlights Its X1 Integration for ESI Collection

By John Patzakis

Recently, Relativity hosted a live webinar featuring the integration of the X1 Distributed Discovery platform with its RelativityOne Collect solution. This X1/Relativity integration enables game-changing efficiencies in the eDiscovery process by accelerating speed to review, and providing an end-to-end process from identification through production. As stated by Relativity Chief Product Officer Chris Brown: “Our exciting new partnership with X1 highlights our continued commitment to providing a streamlined user experience from collection to production…RelativityOne users will be able to combine X1’s innovative endpoint technology with the performance of our SaaS platform, eliminating the cumbersome process of manual data hand-offs and allowing them to get to the pertinent data in their case – faster.”

The webinar featured a live demonstration showing X1 quickly collecting data across multiple custodians and seamlessly importing that data into RelativityOne in minutes. Relativity Collect currently supports Office 365 and Slack sources, and Relativity Product Manager Greg Evans noted that “this X1 integration will now enable Relativity Collect to also reach emails and files on laptops, servers,” and other network sources. The webinar outlined how the Relativity/X1 integration streamlines eDiscovery processes by collapsing the many hand-offs built into current EDRM workflows to provide greater speed and defensibility. Evans also said that new normal of web-enabled collections of remote custodians and data sources was a major driver for the Relativity/X1 alliance, as “remote collections now represent 90 percent of all eDiscovery collections happening right now.”

Adam Rogers, of Complete Discovery Source, a customer of both X1 and RelativityOne, highlighted a recent major multi-national litigation where the X1 and Relativity integration was critical to the success of the project. Adam noted that the effort would have taken about 30 days utilizing traditional methods, “but with this X1 and Relativity integration, we cut it down to 3 days, because with X1, we were able to index everything in-place, search, analyze and categorize that data right away, and then release that data to Relativity for review.”

The live demonstration performed by Greg Evans highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted and efficient search and collection process, with immediate pre-collection visibility into custodial data. X1 Distributed Discovery enhances the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection.

The X1 and Relativity integration addresses several pain points in the existing eDiscovery process. For one, there is currently an inability to quickly and remotely search across and access distributed unstructured data in-place, meaning eDiscovery teams have to spend weeks or even months to collect data as required by other cumbersome solutions. Additionally, using ESI processing methods that involve appliances that are not integrated with the collection will significantly increase cost and time delays.

So in terms of the big picture, with this integration providing a complete platform for efficient data search, eDiscovery and review across the enterprise, organizations will save a lot of time, save a lot of money, and be able to make faster and better decisions. When you accelerate the speed to review and eliminate over-collection, you are going to have much better early insight into your data and increase efficiencies on many levels.

A recording of the X1/Relativity integration webinar can be accessed here.

Leave a comment

Filed under Best Practices, collection, ECA, eDiscovery, Enterprise eDiscovery, ESI

Intelligent ESI Collection Integrated with Relativity Can Cut eDiscovery Costs by 90 Percent

By John Patzakis

One of the biggest drivers of excessive eDiscovery costs is ESI over-collection. This in turn leads to a larger amount of data entering the processing and initial review funnel. These traditional inefficient efforts are manual with numerous hand offs and a high degree of project management and consulting hours to oversee the disjointed workflow. A recent analysis by Compliance CEO Marc Zamsky, illustrated in the chart below, established that cost for collection, processing and first month hosting under a traditional preservation process can cost upwards of $12,000 per custodian:

Properly targeted preservation initiatives are permitted by the courts and can be enabled by next generation software that is able to quickly and effectively access and search these data sources in place and throughout the enterprise. The value of targeted preservation is recognized in the Committee Notes to the recent FRCP amendments, which urge the parties to reach agreement on the preservation of data and the key words, date ranges and other metadata to identify responsive materials. (Citing the Manual for Complex Litigation (MCL) (4th) §40.25(2)). And In re Genetically Modified Rice Litigation, the court noted that “[p]reservation efforts can become unduly burdensome and unreasonably costly unless those efforts are targeted to those documents reasonably likely to be relevant or lead to the discovery of relevant evidence.”

Recently we hosted a webinar with Compliance highlighting the very compelling integration of our X1 Distributed Discovery platform with Relativity. This X1/Relativity integration enables game-changing efficiencies in the eDiscovery process by accelerating speed to review, and providing an end-to-end process from identification through production. As recently stated by Relativity Chief Product Officer Chris Brown: “Our exciting new partnership with X1 highlights our continued commitment to providing a streamlined user experience from collection to production…RelativityOne users will be able to combine X1’s innovative endpoint technology with the performance of our SaaS platform, eliminating the cumbersome process of manual data hand-offs and allowing them to get to the pertinent data in their case – faster.”

The live demonstration highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted and efficient search and collection process, with immediate pre-collection visibility into custodian data. X1 Distributed Discovery significantly streamlines the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection without multiple hand offs, extensive project management and inefficient data processing.

Zamsky commented that the “ability to collect directly from custodian laptops and desktops into a RelativityOne workspace without impacting custodians is a game-changer,” which will “reduce collection times from weeks to hours so that attorneys can quickly begin reviewing and analyzing ESI in RelativityOne.” In fact, Zamsky demonstrated just that by presenting a second chart showing how this streamlined approach, based upon a detailed ROI analysis, reduces eDiscovery costs by over 90 percent:

So in terms of the big picture, with this integration providing a complete platform for efficient data search, eDiscovery, and review across the enterprise, organizations will save a lot of time, save a lot of money, and be able to make faster and better decisions. When you accelerate the speed to review and eliminate over-collection and inefficient processing, you are going to have much better early insight into your data and increase efficiencies on many levels.

A recording of the X1/Relativity integration webinar can be accessed here.

Leave a comment

Filed under Best Practices, collection, eDiscovery, ESI, Uncategorized

Federal Judge: Custodian Self-Collection of ESI is Unethical and Violates Federal Rules of Civil Procedure

By John Patzakis

In E.E.O.C. v. M1 5100 Corp., (S.D. Fla. July 2, 2020), Federal District Judge Matthewman excoriated defense counsel for allowing the practice of unsupervised custodian ESI self-collection, declaring that the practice “greatly troubles and concerns the court.” In this EEOC age discrimination case, two employees of the defendant corporation were permitted to identify and collect their own ESI in an unsupervised manner. Despite no knowledge of the process the client undertook to gather information (which resulted in only 22 pages of documents produced), counsel signed the responses to the RFP’s in violation of FRCP Rule 26(g), which requires that the attorney have knowledge and supervision of the process utilized to collect data from their client in response to discovery requirements.Gavel and books

This notable quote from the opinion provides a very strong legal statement against the practice of ESI custodian self-collection:

“The relevant rules and case law establish that an attorney has a duty and obligation to have knowledge of, supervise, or counsel the client’s discovery search, collection, and production. It is clear to the Court that an attorney cannot abandon his professional and ethical duties imposed by the applicable rules and case law and permit an interested party or person to ‘self-collect’ discovery without any attorney advice, supervision, or knowledge of the process utilized. There is simply no responsible way that an attorney can effectively make the representations required under Rule 26(g)(1) and yet have no involvement in, or close knowledge of, the party’s search, collection and production of discovery…Abdicating completely the discovery search, collection and production to a layperson or interested client without the client’s attorney having sufficient knowledge of the process, or without the attorney providing necessary advice and assistance, does not meet an attorney’s obligation under our discovery rules and case law. Such conduct is improper and contrary to the Federal Rules of Civil Procedure.”

In his ruling, Judge Matthewman stated that he “will not permit an inadequate discovery search, collection and production of discovery, especially ESI, by any party in this case.” He gave the defendant “one last chance to comply with its discovery search, collection and production obligations.”  He then also ordered “the parties to further confer on or before July 9, 2020, to try to agree on relevant ESI sources, custodians, and search terms, as well as on a proposed ESI protocol.” The Court reserved ruling on monetary and evidentiary sanctions pending the results of Defendants second chance efforts.

A Defensible Yet Streamlined Process Is Optimal

EEOC v. M1 5100, is yet another court decision disallowing custodian self-collection of ESI and underscoring the importance of a well-designed and defensible eDiscovery collection process. At the other end of the spectrum, full disk image collection is another preservation option that, while being defensible, is very costly, burdensome and disruptive to operations. Previously in this blog, I discussed at length the numerous challenges associated with full disk imaging.

The ideal solution is a systemized, uniform and defensible process for ESI collection, which also enables targeted and intelligent data collection in support of proportionality principles. Such a capability is only attainable with the right enterprise technology. With X1 Distributed Discovery (X1DD), parties can perform targeted search and collection of the ESI of hundreds of endpoints over the internal network without disrupting operations. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%), thereby bringing much needed feasibility to enterprise-wide eDiscovery collection that can save organizations millions while improving compliance by maintaining metadata, generating audit logs and establishing chain of custody.

And in line with the Judge’s guidance outlined in EEOC v. M1 5100, X1DD provides a repeatable, verifiable and documented process for the requisite defensibility. For a demonstration or briefing on X1 Distributed Discovery, please contact us.

Leave a comment

Filed under Best Practices, Case Law, collection, eDiscovery, ESI, Uncategorized

Lawson v. Spirit Aerosystems: Federal Court Blasts “Bloated” ESI Collection, Rendered TAR Ineffective

By John Patzakis

Technology Assisted Review (TAR), when correctly employed, can significantly reduce legal review costs with generally more accurate results than other traditional legal review processes. However, the benefits associated with TAR are often undercut by the over-collection and over-inclusion of Electronically Stored Information (ESI) into the TAR process. These challenges played out in spades in the recent decision in Lawson v. Spirit Aerosystems, where a Kansas federal judge issued a detailed ruling outlining the parties’ eDiscovery battles, use of Technology Assisted Review (TAR), and whether further TAR costs should be shifted to the Plaintiff. The ex-CEO of Spirit Aerosystems brought his suit accusing Spirit of unlawfully withholding $50 million in retirement benefits over his alleged violation of a non- compete agreement.

Lessons Learned from New Technology-Assisted Review Case Law ...

The Lawson court outlined two ways in particular how ESI over-collection can detrimentally impact TAR. First, the more data introduced into the process, the higher the cost and burden. Some practitioners believe it is necessary to over-collect and subsequently over-include ESI to allow the TAR process to sort everything out. Many service providers charge by volume, so there can be economic incentives that conflict with what is best for the end-client. In some cases, the significant cost savings realized through TAR are erased by eDiscovery costs associated with overly aggressive ESI inclusion on the front end. Per the judge in Lawson, “the TAR set was unnecessarily voluminous because it consisted of the bloated ESI collection” due to overbroad collection parameters.

The court also outlined how the TAR process is much more effective when the initial set of data has a higher richness (also referred to as “prevalence”) ratio. In other words, the higher the rate of responsive data in the initial data set, the better. It has always been understood that document culling is very important to successful, economical document review, and that includes TAR. As noted by Lawson court, “the ‘richness’ of the dataset…can also be a key driver of TAR expenses. This is because TAR is not as simple as loading the dataset and pushing a magic button to identify the relevant and responsive documents. Rather, the parties must devote the resources (usually a combination of attorneys and contract reviewers) necessary to “educate” or “train” the predictive algorithm, typically through an ongoing process…” According to the courts’ decision, the inefficiencies in the process resulted in an estimated TAR bill of $600,000 involving the review of approximately 200 GBs of data. This is far too expensive for TAR to be feasible as a standard litigation process, and the problems all started with the “bloated” ESI collection.

To be sure, the volume of ESI is growing exponentially and will only continue to do so. The costs associated with collecting, processing, reviewing, and producing documents in litigation are the source of considerable pain for litigants, including the Plaintiff in Lawson, who will, per the courts’ ruling, incur at least a substantial amount of the TAR bill under the cost-shifting order. The only way to reduce that pain to its minimum is to use all tools available in all appropriate circumstances within the bounds of reasonableness and proportionality to control the volumes of data that enter the discovery pipeline, including TAR.

Ideally, an effective and targeted collection capability can enable parties to ultimately process, host, review and produce less ESI.  This capability should enable a pre-collection early case assessment capability (ECA) to foster cooperation and proportionality in discovery by informing the parties early in the process about where relevant ESI is located and what ESI is significant to the case. And with such benefits also comes a much more improved TAR process. X1 Distributed Discovery (X1DD) uniquely fulfills this requirement with its ability to perform pre-collection early case assessment, instead of ECA after the costly, time consuming and disruptive collection phase, thereby providing a game-changing new approach to the traditional eDiscovery model.  X1DD enables enterprises to quickly and easily search across hundreds of distributed endpoints from a central location.  This allows organizations to easily perform unified complex searches across content, metadata, or both and obtain full results in minutes, enabling true pre-collection ECA with live keyword analysis and distributed processing and collection in parallel at the custodian level. To be sure, this dramatically shortens the identification/collection process by weeks if not months, curtails processing and review costs from not over-collecting data, and provides confidence to the legal team with a highly transparent, consistent and systemized process. And now we know of another key benefit of an effective collection and ECA process: much more accurate and feasible technology assisted review.

Leave a comment

Filed under Best Practices, Case Law, Case Study, collection, ECA, eDiscovery, Enterprise eDiscovery, ESI